Outlier Detection

Outlier Detection is a task of identifying a subset of a given data set which are considered anomalous in that they are unusual from other instances. It is one of the core data mining tasks and is central to many applications. In the security field, it can be used to identify potentially threatening users, in the manufacturing field it can be used to identify parts that are likely to fail.

Source: Coverage-based Outlier Explanation

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 101–110 of 703 papers

Title	Date	Tasks	Status	Hype
About Test-time training for outlier detection	Apr 4, 2024	Outlier Detection	—Unverified	0
Hyperbolic Metric Learning for Visual Outlier Detection	Mar 22, 2024	Metric LearningOutlier Detection	—Unverified	0
Automatic Outlier Rectification via Optimal Transport	Mar 21, 2024	Outlier Detection	—Unverified	0
Validating and Exploring Large Geographic Corpora	Mar 13, 2024	Language IdentificationOutlier Detection	—Unverified	0
Interactive Continual Learning: Fast and Slow Thinking	Mar 5, 2024	Continual LearningOutlier Detection	CodeCode Available	2
Outlier-Detection for Reactive Machine Learned Potential Energy Surfaces	Feb 27, 2024	Outlier DetectionUncertainty Quantification	CodeCode Available	0
Outlier detection by ensembling uncertainty with negative objectness	Feb 23, 2024	Outlier DetectionPrediction	CodeCode Available	1
A Comprehensive System for Secondary Structure Analysis of Protein Models	Feb 18, 2024	Outlier Detection	—Unverified	0
Can Tree Based Approaches Surpass Deep Learning in Anomaly Detection? A Benchmarking Study	Feb 11, 2024	Anomaly DetectionBenchmarking	CodeCode Available	0
Can we predict QPP? An approach based on multivariate outliers	Feb 7, 2024	Outlier Detection	—Unverified	0

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All datasets ECG5000 Balance scale_class 1 Breast cancer Wisconsin_class 2 Breast cancer Wisconsin_class 4 Fashion-MNIST Glass identification Heart-C Hepatitis Internet Ad Ionosphere_class b SKAB

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	VRAE+SVM	Accuracy	0.98	—	Unverified
2	F-t ALSTM-FCN	Accuracy	0.95	—	Unverified
3	GENDIS	Accuracy	0.94	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	99.03	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	37.62	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	65.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PAE	AUROC	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	99.05	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MIX	AUC	0.86	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MIX	AUC-ROC	0.85	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MIX	AUC-ROC	0.93	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	86.33	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LSTMCaps	Average F1	0.74	—	Unverified